Loading [MathJax]/extensions/tex2jax.js
Joint MU-MIMO Precoding and Computation Optimization for Energy Efficient Industrial IoT With Mobile Edge Computing | IEEE Journals & Magazine | IEEE Xplore

Joint MU-MIMO Precoding and Computation Optimization for Energy Efficient Industrial IoT With Mobile Edge Computing

Publisher: IEEE

Abstract:

In the fourth industrial revolution, the industrial Internet of Things (IIoT) will bring fundamental changes to human communities. This paper proposes to make full use of...View more

Abstract:

In the fourth industrial revolution, the industrial Internet of Things (IIoT) will bring fundamental changes to human communities. This paper proposes to make full use of the under-utilized computing resources of wired edge devices to alleviate the computing burden of the processing center in delay-constrained multi-user networks. Our goal is to minimize the weighted energy consumption while ensuring the required latency. The formulated problems are NP-hard involving joint optimization of the computation task assignment, transmit association design, multiple-input multiple-output (MIMO) precoding, and computing resource allocation with binary and partial offloading protocols. By utilizing the weighted minimum mean-squared-error method, quadratic transformation, and difference of convex functions algorithm, we propose two joint computation offloading and resource allocation algorithms for binary and partial offloading protocols, respectively. Simulation results confirm the efficiency of the proposed algorithms and demonstrate that the proposed algorithms achieve a significant computation performance enhancement.
Published in: IEEE Transactions on Green Communications and Networking ( Volume: 7, Issue: 3, September 2023)
Page(s): 1472 - 1485
Date of Publication: 28 March 2023
Electronic ISSN: 2473-2400
Publisher: IEEE

Funding Agency:


References

References is not available for this document.